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基于神经网络的单相自适应重合闸的研究
The Study on Single-pole Adaptive Reclosure Based on Neural Network
【摘要】 自适应自动重合闸技术具有诸多传统重合闸技术所不具有的优势。将人工神经网络理论应用于单相自适应重合闸中,建立了一个3层的前向网络模型。利用MATLAB软件进行了大量仿真实验,验证了其在带并联电抗器的超高压长输电线路的瞬时性故障与永久性故障的识别中具有良好的可行性。
【Abstract】 Adaptive single-pole auto-reclosure offers many advantages over the conventional approach.In the paper,an artificial neural network is applied to the single-pole adaptive reclosure and a three-layer feed-forward neural network model is established.The results of simulation by MATLAB show that this method is valid to distinguish the transient faults and permanent faults on transmission line with shunt reactors.
【关键词】 单相自适应重合闸;
瞬时性故障;
永久性故障;
人工神经网络;
【Key words】 Single-pole adaptive reclosure; Transient fault; Permanent fault; Artificial neural network;
【Key words】 Single-pole adaptive reclosure; Transient fault; Permanent fault; Artificial neural network;
- 【文献出处】 东北电力学院学报 ,Journal of Northeast China Institute of Electric Power Engineering(Natural Science Edition) , 编辑部邮箱 ,2005年02期
- 【分类号】TM762
- 【被引频次】22
- 【下载频次】142